Academic Procrastination in Two Settings: Motivation Correlates,Behavioral Patterns,and Negative Impact of Procrastination in Canada and Singapore

Two studies are reported examining academic procrastination and motivation in 1,145 university students from Canada and Singapore. In Study 1, relationships between procrastination and motivation variables were found to be similar across contexts, with self‐efficacy for self‐regulated learning most strongly associated with procrastination in both contexts. In Study 2, patterns of procrastinating behavior and the negative impact of procrastination were examined and compared in Canadian and Singaporean undergraduates. Participants in both contexts reported writing to be the academic task most prone to procrastination. More Singaporeans than Canadians were classified as negative procrastinators (i.e. rated procrastination as a negative influence on academic functioning). In both contexts, negative procrastinators spent more time procrastinating than neutral procrastinators and displayed lower self‐efficacy for self‐regulated learning. On décrit deux recherches portant sur la motivation et la procrastination universitaire (tendance à remettre au lendemain) de 1145 étudiants du Canada et de Singapour. Dans la première étude, les relations entre la motivation et la procrastination sont apparues être analogues dans les deux pays, la variable la plus fortement associéà la procrastination étant l'auto‐efficience pour l'apprentissage autorégulé. Dans la deuxième étude, les schémas comportementaux de procrastination et son impact négatif ont été analysés et comparés chez les étudiants de 1° cycle canadiens et singapouriens. Les sujets des deux pays ont mentionné la rédaction comme étant la tâche universitaire la plus soumise à la procrastination. Davantage de Singapouriens que de Canadiens été classés en procrastinateurs négatifs (c'est‐à‐dire que la procrastination est considérée comme étant un handicap pour les études). Dans les deux cas, les procrastinateurs négatifs gaspillaient plus de temps que les procrastinateurs neutres et manifestaient une moindre auto‐efficience pour l'apprentissage autorégulé.     

Identifying subgroups that succeed or fail with three levels of physical activity intervention: the Activity Counseling Trial.

The authors used recursive partitioning methods to identify combinations of baseline characteristics that predict 2-year physical activity success in each of 3 physical activity interventions delivered in the multisite Activity Counseling Trial. The sample consisted of 874 initially sedentary primary care patients, ages 35-75 years, who were at risk for cardiovascular disease. Predictors of 2-year success were specific to each intervention and represented a range of domains, including physiological, demographic, psychosocial, health-related, and environmental variables. The results indicate how specific patient subgroups (e.g., obese, unfit individuals; high-income individuals in stable health) may respond differently to varying levels and amounts of professional assistance and support. The methods used provide a practical first step toward identifying clinically meaningful patient subgroups for further systematic investigation.     

A quantitative analysis of the relationship between the Cook-Medley Hostility Scale and traditional coronary artery disease risk factors.

One possible explanation for the association between Cook-Medley Hostility Scale (Ho Scale; W. W. Cook & D. M. Medley, 1954) scores and premature coronary artery disease (CAD) morbidity and mortality is that hostile persons also have elevations on CAD risk factors. Meta-analyses with fixed and random-effects models were used to evaluate the relationship between Ho Scale scores and CAD risk factors in the empirical literature. Ho Scale scores were significantly related to body mass index, waist-to-hip ratio, insulin resistance, lipid ratio, triglycerides, glucose, socioeconomic status (SES), alcohol consumption, and smoking. Although there was also heterogeneity among study outcomes, the results of conservative random effects models provide confidence in the obtained relationships. On the basis of available evidence, researchers might give attention to obesity, insulin resistance, damaging health behaviors, and SES as potential contributing factors in understanding the association between Ho Scale scores and CAD.